With communication technologies advanced recently, a great variety of electronic devices such as a mobile phone, a smart phone, a tablet PC, and the like are increasingly popularized due to their high usability and good portability. Nowadays, many manufacturers of electronic devices have grown very attentive to recognition technology capable of using much more intuitively a function provided by electronic devices. Particularly, recognition technology of a non-contact type is widely used in various electronic devices.
Non-contact type recognition technology may include facial recognition, iris recognition, motion recognition, and the like. Normally this non-contact type recognition technology has a process of extracting or tracking information associated with user's behavior or action and a process of identifying a user input by comparing the extracted information with matched data. Unfortunately, non-contact type recognition technology may often have a difficulty in exactly extracting information associated with user's behavior or action, thus failing to obtain a reliable user input. Specifically, an electronic device having a recognition function may provide default data necessary for pattern recognition matching at the manufacture thereof. Such default values are, however, set on the basis of generalized information. This causes a failure to reflect characteristics of individual users and thus deteriorates the rate of recognition. For example, an eye pattern required for eye recognition is set to a normal size as a default value. However, in actual, users' eye sizes may be often greater or smaller than a normal size. Therefore, recognition functions provided by an electronic device fail to directly reflect characteristics of individual users, and this causes a poor rate of recognition.